183 research outputs found

    Bayesian variable selection and survival modeling: assessing the Most important comorbidities that impact lung and colorectal cancer survival in Spain

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    ancer survival represents one of the main indicators of interest in cancer epidemiology. However, the survival of cancer patients can be affected by several factors, such as comorbidities, that may interact with the cancer biology. Moreover, it is interesting to understand how different cancer sites and tumour stages are affected by different comorbidities. Identifying the comorbidities that affect cancer survival is thus of interest as it can be used to identify factors driving the survival of cancer patients. This information can also be used to identify vulnerable groups of patients with comorbidities that may lead to worst prognosis of cancer. We address these questions and propose a principled selection and evaluation of the effect of comorbidities on the overall survival of cancer patients. In the first step, we apply a Bayesian variable selection method that can be used to identify the comorbidities that predict overall survival. In the second step, we build a general Bayesian survival model that accounts for time-varying effects. In the third step, we derive several posterior predictive measures to quantify the effect of individual comorbidities on the population overall survival. We present applications to data on lung and colorectal cancers from two Spanish population-based cancer registries. The proposed methodology is implemented with a combination of the R-packages mombf and rstan. We provide the code for reproducibility at https://github.com/migariane/BayesVarImpComorbiCancer

    Poor sleep quality, antepartum depression and suicidal ideation among pregnant women.

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    To evaluate the independent and combined associations of maternal self-reported poor sleep quality and antepartum depression with suicidal ideation during the third trimester METHODS: A cross-sectional study was conducted among 1298 pregnant women (between 24 and 28 gestational weeks) attending prenatal clinics in Lima, Peru. Antepartum depression and suicidal ideation were assessed using the Patient Health Questionnaire-9 (PHQ-9). The Pittsburgh Sleep Quality Index (PSQI) questionnaire was used to assess sleep quality. Multivariate logistical regression procedures were used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) after adjusting for putative confounders. Approximately, 17% of women were classified as having poor sleep quality (defined using the recommended criteria of PSQI global score of >5 vs. ≤5). Further, the prevalence of antepartum depression and suicidal ideation were 10.3% and 8.5%, respectively in this cohort. After adjusting for confounders including depression, poor sleep quality was associated with a 2.81-fold increased odds of suicidal ideation (OR=2.81; 95% CI 1.78-4.45). When assessed as a continuous variable, each 1-unit increase in the global PSQI score resulted in a 28% increase in odds for suicidal ideation, even after adjusting for depression (OR=1.28; 95% CI 1.15-1.41). The odds of suicidal ideation was particularly high among depressed women with poor sleep quality (OR=13.56 95% CI 7.53-24.41) as compared with women without either risk factor. This cross-sectional study utilized self-reported data. Causality cannot be inferred, and results may not be fully generalizable. Poor sleep quality, even after adjusting for depression, is associated with antepartum suicidal ideation. Our findings support the need to explore sleep-focused interventions for pregnant women

    Elevation and cholera: an epidemiological spatial analysis of the cholera epidemic in Harare, Zimbabwe, 2008-2009

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    BACKGROUND: In highly populated African urban areas where access to clean water is a challenge, water source contamination is one of the most cited risk factors in a cholera epidemic. During the rainy season, where there is either no sewage disposal or working sewer system, runoff of rains follows the slopes and gets into the lower parts of towns where shallow wells could easily become contaminated by excretes. In cholera endemic areas, spatial information about topographical elevation could help to guide preventive interventions. This study aims to analyze the association between topographic elevation and the distribution of cholera cases in Harare during the cholera epidemic in 2008 and 2009. METHODS: We developed an ecological study using secondary data. First, we described attack rates by suburb and then calculated rate ratios using whole Harare as reference. We illustrated the average elevation and cholera cases by suburbs using geographical information. Finally, we estimated a generalized linear mixed model (under the assumption of a Poisson distribution) with an Empirical Bayesian approach to model the relation between the risk of cholera and the elevation in meters in Harare. We used a random intercept to allow for spatial correlation of neighboring suburbs. RESULTS: This study identifies a spatial pattern of the distribution of cholera cases in the Harare epidemic, characterized by a lower cholera risk in the highest elevation suburbs of Harare. The generalized linear mixed model showed that for each 100 meters of increase in the topographical elevation, the cholera risk was 30% lower with a rate ratio of 0.70 (95% confidence interval=0.66-0.76). Sensitivity analysis confirmed the risk reduction with an overall estimate of the rate ratio between 20% and 40%. CONCLUSION: This study highlights the importance of considering topographical elevation as a geographical and environmental risk factor in order to plan cholera preventive activities linked with water and sanitation in endemic areas. Furthermore, elevation information, among other risk factors, could help to spatially orientate cholera control interventions during an epidemic

    Investigating the inequalities in route to diagnosis amongst patients with diffuse large B-cell or follicular lymphoma in England

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    Introduction: Diagnostic delay is associated with lower chances of cancer survival. Underlying comorbidities are known to affect the timely diagnosis of cancer. Diffuse large B-cell (DLBCL) and follicular lymphomas (FL) are primarily diagnosed amongst older patients, who are more likely to have comorbidities. Characteristics of clinical commissioning groups (CCG) are also known to impact diagnostic delay. We assess the association between comorbidities and diagnostic delay amongst patients with DLBCL or FL in England during 2005–2013. Methods: Multivariable generalised linear mixed-effect models were used to assess the main association. Empirical Bayes estimates of the random effects were used to explore between-cluster variation. The latent normal joint modelling multiple imputation approach was used to account for partially observed variables. Results: We included 30,078 and 15,551 patients diagnosed with DLBCL or FL, respectively. Amongst patients from the same CCG, having multimorbidity was strongly associated with the emergency route to diagnosis (DLBCL: odds ratio 1.56, CI 1.40–1.73; FL: odds ratio 1.80, CI 1.45–2.23). Amongst DLBCL patients, the diagnostic delay was possibly correlated with CCGs that had higher population densities. Conclusions: Underlying comorbidity is associated with diagnostic delay amongst patients with DLBCL or FL. Results suggest a possible correlation between CCGs with higher population densities and diagnostic delay of aggressive lymphomas

    Summarizing and communicating on survival data according to the audience: a tutorial on different measures illustrated with population-based cancer registry data

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    Aurélien Belot, Aminata Ndiaye, Miguel-Angel Luque-Fernandez, Dimitra-Kleio Kipourou, Camille Maringe, Francisco Javier Rubio, Bernard Rachet Cancer Survival Group, Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK Abstract: Survival data analysis results are usually communicated through the overall survival probability. Alternative measures provide additional insights and may help in communicating the results to a wider audience. We describe these alternative measures in two data settings, the overall survival setting and the relative survival setting, the latter corresponding to the particular competing risk setting in which the cause of death is unavailable or unreliable. In the overall survival setting, we describe the overall survival probability, the conditional survival probability and the restricted mean survival time (restricted to a prespecified time window). In the relative survival setting, we describe the net survival probability, the conditional net survival probability, the restricted mean net survival time, the crude probability of death due to each cause and the number of life years lost due to each cause over a prespecified time window. These measures describe survival data either on a probability scale or on a timescale. The clinical or population health purpose of each measure is detailed, and their advantages and drawbacks are discussed. We then illustrate their use analyzing England population-based registry data of men 15–80 years old diagnosed with colon cancer in 2001–2003, aiming to describe the deprivation disparities in survival. We believe that both the provision of a detailed example of the interpretation of each measure and the software implementation will help in generalizing their use. Keywords: survival, competing risks, relative survival setting, conditional survival, restricted mean survival time, net survival, crude probability of death, number of life years los

    The pattern of Comorbidities and Associated Risk Factors among Colorectal Cancer Patients in Spain: CoMCoR study

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    AbstractColorectal cancer is the second most frequently diagnosed cancer in Spain. Cancer treatment and outcomes can be influenced by tumor characteristics, patient general health status and comorbidities. Numerous studies have analyzed the influence of comorbidity on cancer outcomes, but limited information is available regarding the frequency and distribution of comorbidities in colorectal cancer patients, particularly elderly ones, in the Spanish population. We developed a population-based high-resolution cohort study of all incident colorectal cancer cases diagnosed in Spain in 2011 to describe the frequency and distribution of comorbidities, as well as tumor and healthcare factors. We then characterized risk factors associated with the most prevalent comorbidities, as well as dementia and multimorbidity, and developed an interactive web application to visualize our findings. The most common comorbidities were diabetes (23.6%), chronic obstructive pulmonary disease (17.2%), and congestive heart failure (14.5%). Dementia was the most common comorbidity among patients aged ≥75 years. Patients with dementia had a 30% higher prevalence of being diagnosed at stage IV and the highest prevalence of emergency hospital admission after colorectal cancer diagnosis (33%). Colorectal cancer patients with dementia were nearly three times more likely to not be offered surgical treatment. Age ≥75 years, obesity, male sex, being a current smoker, having surgery more than 60 days after cancer diagnosis, and not being offered surgical treatment were associated with a higher risk of multimorbidity. Patients with multimorbidity aged ≥75 years showed a higher prevalence of hospital emergency admission followed by surgery the same day of the admission (37%). We found a consistent pattern in the distribution and frequency of comorbidities and multimorbidity among colorectal cancer patients. The high frequency of stage IV diagnosis among patients with dementia and the high proportion of older patients not being offered surgical treatment are significant findings that require policy actions.</jats:p

    Multimorbidity by Patient and Tumor Factors and Time-to-Surgery Among Colorectal Cancer Patients in Spain: A Population-Based Study.

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    BACKGROUND: Cancer treatment and outcomes can be influenced by tumor characteristics, patient overall health status, and comorbidities. While previous studies have analyzed the influence of comorbidity on cancer outcomes, limited information is available regarding factors associated with the increased prevalence of comorbidities and multimorbidity among patients with colorectal cancer in Spain. PATIENTS AND METHODS: This cross-sectional study obtained data from all colorectal cancer cases diagnosed in two Spanish provinces in 2011 from two population-based cancer registries and electronic health records. We calculated the prevalence of comorbidities according to patient and tumor factors, identified factors associated with an increased prevalence of comorbidity and multimorbidity, analyzed the association between comorbidities and time-to-surgery, and developed an interactive web application (https://comcor.netlify.com/). RESULTS: The most common comorbidities were diabetes (23.6%), chronic obstructive pulmonary disease (17.2%), and congestive heart failure (14.5%). Among all comorbidities, 52% of patients were diagnosed at more advanced stages (stage III/IV). Patients with advanced age, restricted performance status or who were disabled, obese, and smokers had a higher prevalence of multimorbidity. Patients with multimorbidity had a longer time-to-surgery than those without comorbidity (17 days, 95% confidence interval: 3-29 days). CONCLUSION: We identified a consistent pattern of factors associated with a higher prevalence of comorbidities and multimorbidity at diagnosis and an increased time-to-surgery among patients with colorectal cancer with multimorbidity in Spain. This pattern may provide insights for further etiological and preventive research and help to identify patients at a higher risk for poorer cancer outcomes and suboptimal treatment

    Multimorbidity and short-term overall mortality among colorectal cancer patients in Spain: A population-based cohort study.

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    BACKGROUND: Numerous studies have analysed the effect of comorbidity on cancer outcomes, but evidence on the association between multimorbidity and short-term mortality among colorectal cancer patients is limited. We aimed to assess this association and the most frequent patterns of multimorbidity associated with a higher short-term mortality risk among colorectal cancer patients in Spain. METHODS: Data were obtained from two Spanish population-based cancer registries and electronic health records. We estimated the unadjusted cumulative incidence of death by comorbidity status at 6 months and 1 year. We used a flexible parametric model to derive the excess mortality hazard ratios (HRs) for multimorbidity after adjusting for sex, age at diagnosis, cancer stage and treatment. We estimated the adjusted cumulative incidence of death by comorbidity status and identified multimorbidity patterns. RESULTS: Among the study participants, 1,048 cases were diagnosed with cancers of the colon and rectum, 2 cases with cancer of the anus with overlapping sites of the rectum and 11 cases with anal adenocarcinomas but treated as colorectal cancer patients. Among 1,061 colorectal cancer patients, 171 (16.2%) died before 6 months, 246 (23.3%) died before the 1-year follow-up, and 324 (30.5%) had multimorbidity. Patients with multimorbidity had two times higher mortality risk than those without comorbidities at 6 months (adjusted HR: 2.04; 95% confidence interval [CI]: 1.30-3.20, p = 0.002). The most frequent multimorbidity pattern was congestive heart failure + diabetes. However, patients with rheumatologic disease + diabetes had two times higher 1-year mortality risk than those without comorbidities (HR: 2.23; 95% CI: 1.23-4.07, p = 0.008). CONCLUSIONS: Multimorbidity was a strong independent predictor of short-term mortality at 6 months and 1 year among the colorectal cancer patients in Spain. The identified multimorbidity pattern was consistent. Our findings might help identify patients at a higher risk for poor cancer and treatment outcomes

    Plasma Glycated CD59, a Novel Biomarker for Detection of Pregnancy-Induced Glucose Intolerance.

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    OBJECTIVE: Plasma glycated CD59 (pGCD59) is an emerging biomarker in diabetes. We assessed whether pGCD59 could predict the following: the results of the glucose challenge test (GCT) for screening of gestational diabetes mellitus (GDM) (primary analysis); and the diagnosis of GDM and prevalence of large for gestational age (LGA) newborns (secondary analyses). RESEARCH DESIGN AND METHODS: Case-control study of 1,000 plasma samples from women receiving standard prenatal care, 500 women having a normal GCT (control subjects) and 500 women with a failed GCT and a subsequent oral glucose tolerance test (case patients). RESULTS: Compared with control subjects, the median (interquartile range) pGCD59 value was 8.5-fold higher in case patients and 10-fold higher in GDM patients, as follows: control subjects 0.33 (0.19); case patients 2.79 (1.4); GDM patients 3.23 (1.43) (P < 0.001); area under the receiver operating characteristic curve 0.92. LGA prevalence was 4.3% in the lowest quartile and 13.5% in the highest quartile of pGCD59. CONCLUSIONS: One pGCD59 measurement during weeks 24-28 identifies pregnancy-induced glucose intolerance with high sensitivity and specificity and can potentially identify the risk for LGA

    Diarrhea is a Major killer of Children with Severe Acute Malnutrition Admitted to Inpatient Set-up in Lusaka, Zambia

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    <p>Abstract</p> <p>Introduction</p> <p>Mortality of children with Severe Acute Malnutrition (SAM) in inpatient set-ups in sub-Saharan Africa still remains unacceptably high. We investigated the prevalence and effect of diarrhea and HIV infection on inpatient treatment outcome of children with complicated SAM receiving treatment in inpatient units.</p> <p>Method</p> <p>A cohort of 430 children aged 6-59 months old with complicated SAM admitted to Zambia University Teaching Hospital's stabilization centre from August to December 2009 were followed. Data on nutritional status, socio-demographic factors, and admission medical conditions were collected up on enrollment. T-test and chi-square tests were used to compare difference in mean or percentage values. Logistic regression was used to assess risk of mortality by admission characteristics.</p> <p>Results</p> <p>Majority, 55.3% (238/430) were boys. The median age of the cohort was 17 months (inter-quartile range, IQR 12-22). Among the children, 68.9% (295/428) had edema at admission. The majority of the children, 67.3% (261/388), presented with diarrhea; 38.9% (162/420) tested HIV positive; and 40.5% (174/430) of the children died. The median Length of stay of the cohort was 9 days (IQR, 5-14 days); 30.6% (53/173) of the death occurred within 48 hours of admission. Children with diarrhea on admission had two and half times higher odds of mortality than those without diarrhea; Adjusted OR = 2.5 (95% CI 1.50-4.09, P < 0.001). The odds of mortality for children with HIV infection was higher than children without HIV infection; Adjusted OR = 1.6 (95% CI 0.99-2.48 P = 0.5).</p> <p>Conclusion</p> <p>Diarrhea is a major cause of complication in children with severe acute malnutrition. Under the current standard management approach, diarrhea in children with SAM was found to increase their odds of death substantially irrespective of other factors.</p
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